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jinaai
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jina-embedding-s-en-v1

Sentence Similarity
sentence-transformers
PyTorch
English
t5
finetuner
mteb
feature-extraction
custom_code
Eval Results
Inference Endpoints
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@@ -49,11 +49,11 @@ We compared the model against `all-minilm-l6-v2` from sbert and `text-embeddings
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  |Name|STS12|STS13|STS14|STS15|STS16|STS17|TRECOVID|Quora|SciFact|param |context|
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- |------------------------------|-----|-----|-----|-----|-----|-----|--------|-----|-------|---------|------|
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- |all-minilm-l6-v2|0.724|0.806|0.756|0.854|0.79 |0.876|0.473 |0.876|0.645 |33m |256|
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- |all-mpnet--base-v2|0.726|0.835|0.78 |0.857|0.8 |0.906|0.513 |0.875|0.656 |110m |256|
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- |ada-embedding-002|0.698|0.833|0.761|0.861|0.86 |0.903|0.685 |0.876|0.726 |Unknown API based |8192|
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- |jina-embedding-small|0.738|0.781|0.732|0.833|0.785|0.859|0.471 |0.852|0.567 |35m |512|
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  For more tasks and metrics, please checkout [MTEB](https://huggingface.co/spaces/mteb/leaderboard) benchmark.
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  |Name|STS12|STS13|STS14|STS15|STS16|STS17|TRECOVID|Quora|SciFact|param |context|
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+ |------------------------------|-----|-----|-----|-----|-----|-----|--------|-----|-------|
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+ |all-minilm-l6-v2|0.724|0.806|0.756|0.854|0.79 |0.876|0.473 |0.876|0.645 |
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+ |all-mpnet--base-v2|0.726|0.835|0.78 |0.857|0.8 |0.906|0.513 |0.875|0.656 |
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+ |ada-embedding-002|0.698|0.833|0.761|0.861|0.86 |0.903|0.685 |0.876|0.726 |
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+ |jina-embedding-small|0.738|0.781|0.732|0.833|0.785|0.859|0.471 |0.852|0.567 |
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  For more tasks and metrics, please checkout [MTEB](https://huggingface.co/spaces/mteb/leaderboard) benchmark.
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